Combined ChatWaifuCN.py and ChatWaifuJP.py

ChatWaifu.py

@@ -0,0 +1,217 @@
+from scipy.io.wavfile import write
+from mel_processing import spectrogram_torch
+from text import text_to_sequence, _clean_text
+from models import SynthesizerTrn
+import utils
+import commons
+import sys
+import re
+from torch import no_grad, LongTensor
+import logging
+from winsound import PlaySound
+
+chinese_model_path = ".\model\CN\model.pth"
+chinese_config_path = ".\model\CN\config.json"
+japanese_model_path = ".\model\H_excluded.pth"
+japanese_config_path = ".\model\config.json"
+
+####################################
+#CHATGPT INITIALIZE
+from pyChatGPT import ChatGPT
+import json
+
+modelmessage = """ID      Model
+0       Chinese
+1       Japanese
+"""
+
+idmessage = """ID      Speaker
+0       綾地寧々
+1       在原七海
+2       小茸
+3       唐乐吟
+"""
+speakerID = 0
+
+def get_input():
+    # prompt for input
+    print("You:")
+    user_input = input()
+    return user_input
+
+def get_input_jp():
+    # prompt for input
+    print("You:")
+    user_input = input() +" 使用日本语"
+    return user_input
+
+def get_token():
+    token = input("Copy your token from ChatGPT and press Enter \n")
+    return token
+
+
+################################################
+
+
+logging.getLogger('numba').setLevel(logging.WARNING)
+
+
+def ex_print(text, escape=False):
+    if escape:
+        print(text.encode('unicode_escape').decode())
+    else:
+        print(text)
+
+
+def get_text(text, hps, cleaned=False):
+    if cleaned:
+        text_norm = text_to_sequence(text, hps.symbols, [])
+    else:
+        text_norm = text_to_sequence(text, hps.symbols, hps.data.text_cleaners)
+    if hps.data.add_blank:
+        text_norm = commons.intersperse(text_norm, 0)
+    text_norm = LongTensor(text_norm)
+    return text_norm
+
+
+def ask_if_continue():
+    while True:
+        answer = input('Continue? (y/n): ')
+        if answer == 'y':
+            break
+        elif answer == 'n':
+            sys.exit(0)
+
+
+def print_speakers(speakers, escape=False):
+    if len(speakers) > 100:
+        return
+    print('ID\tSpeaker')
+    for id, name in enumerate(speakers):
+        ex_print(str(id) + '\t' + name, escape)
+
+
+def get_speaker_id(message):
+    speaker_id = input(message)
+    try:
+        speaker_id = int(speaker_id)
+    except:
+        print(str(speaker_id) + ' is not a valid ID!')
+        sys.exit(1)
+    return speaker_id
+
+
+def get_label_value(text, label, default, warning_name='value'):
+    value = re.search(rf'\[{label}=(.+?)\]', text)
+    if value:
+        try:
+            text = re.sub(rf'\[{label}=(.+?)\]', '', text, 1)
+            value = float(value.group(1))
+        except:
+            print(f'Invalid {warning_name}!')
+            sys.exit(1)
+    else:
+        value = default
+    return value, text
+
+
+def get_label(text, label):
+    if f'[{label}]' in text:
+        return True, text.replace(f'[{label}]', '')
+    else:
+        return False, text
+
+
+
+def generateSound(inputString, id, model_id):
+    if '--escape' in sys.argv:
+        escape = True
+    else:
+        escape = False
+
+    #model = input('0: Chinese')
+    #config = input('Path of a config file: ')
+    if model_id == 0:
+        model = chinese_model_path
+        config = chinese_config_path
+    elif model_id == 1:
+        model = japanese_model_path
+        config = japanese_config_path
+
+
+    hps_ms = utils.get_hparams_from_file(config)
+    n_speakers = hps_ms.data.n_speakers if 'n_speakers' in hps_ms.data.keys() else 0
+    n_symbols = len(hps_ms.symbols) if 'symbols' in hps_ms.keys() else 0
+    emotion_embedding = hps_ms.data.emotion_embedding if 'emotion_embedding' in hps_ms.data.keys() else False
+
+    net_g_ms = SynthesizerTrn(
+        n_symbols,
+        hps_ms.data.filter_length // 2 + 1,
+        hps_ms.train.segment_size // hps_ms.data.hop_length,
+        n_speakers=n_speakers,
+        emotion_embedding=emotion_embedding,
+        **hps_ms.model)
+    _ = net_g_ms.eval()
+    utils.load_checkpoint(model, net_g_ms)
+
+    if n_symbols != 0:
+        if not emotion_embedding:
+            #while True:
+            if(1 == 1):
+                choice = 't'
+                if choice == 't':
+                    text = inputString
+                    if text == '[ADVANCED]':
+                        text = "我不会说"
+
+                    length_scale, text = get_label_value(
+                        text, 'LENGTH', 1, 'length scale')
+                    noise_scale, text = get_label_value(
+                        text, 'NOISE', 0.667, 'noise scale')
+                    noise_scale_w, text = get_label_value(
+                        text, 'NOISEW', 0.8, 'deviation of noise')
+                    cleaned, text = get_label(text, 'CLEANED')
+
+                    stn_tst = get_text(text, hps_ms, cleaned=cleaned)
+
+                    speaker_id = id 
+                    out_path = "output.wav"
+
+                    with no_grad():
+                        x_tst = stn_tst.unsqueeze(0)
+                        x_tst_lengths = LongTensor([stn_tst.size(0)])
+                        sid = LongTensor([speaker_id])
+                        audio = net_g_ms.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=noise_scale,
+                                               noise_scale_w=noise_scale_w, length_scale=length_scale)[0][0, 0].data.cpu().float().numpy()
+
+                write(out_path, hps_ms.data.sampling_rate, audio)
+                print('Successfully saved!')
+
+if __name__ == "__main__":
+    session_token = get_token()
+    api = ChatGPT(session_token)
+    print(modelmessage)
+    model_id = int(input('选择回复语言: '))
+    print("\n" + idmessage)
+    id = get_speaker_id('选择角色: ')
+    print()
+    while True:
+
+        if model_id == 0:
+            resp = api.send_message(get_input())
+            if(resp == "quit()"):
+                break
+            answer = resp["message"].replace('\n','')
+            print("ChatGPT:")
+            print(answer)
+            generateSound("[ZH]"+answer+"[ZH]", id, model_id)
+            PlaySound(r'.\output.wav', flags=1)
+        elif model_id == 1:
+            resp = api.send_message(get_input_jp())
+            if(resp == "quit()"):
+                break
+            answer = resp["message"].replace('\n','')
+            print("ChatGPT:")
+            print(answer)
+            generateSound(answer, id, model_id)
+            PlaySound(r'.\output.wav', flags=1)